Low coverage whole genome sequencing of low-grade dysplasia strongly predicts colorectal cancer risk in ulcerative colitis

Abstract

Patients with inflammatory bowel disease (IBD) are at increased risk of colorectal cancer (CRC), and this risk increases dramatically in those who develop low-grade dysplasia (LGD). However, there is currently no accurate way to risk-stratify patients with LGD, leading to both over- and under-treatment of cancer risk. Here we show that the burden of somatic copy number alterations (CNAs) within resected LGD lesions strongly predicts future cancer development. We performed a retrospective multi-centre validated case-control study of n=122 patients (40 progressors, 82 non-progressors, 270 LGD regions). Low coverage whole genome sequencing revealed CNA burden was significantly higher in progressors than non-progressors (p=2×10^-6 in discovery cohort) and was a very significant predictor of CRC risk in univariate analysis (odds ratio = 36; p=9×10^-7), outperforming existing clinical risk factors such as lesion size, shape and focality. Optimal risk prediction was achieved with a multivariate model combining CNA burden with the known clinical risk factor of incomplete LGD resection. The measurement of CNAs in LGD lesions is a robust, low-cost and rapidly translatable predictor of CRC risk in IBD that can be used to direct management and so prevent CRC in high-risk individuals whilst sparing those at low-risk from unnecessary intervention.

Figure 1:. Study design.

Schematic showing the detection and removal of low-grade dysplasia during routine IBD surveillance, with progressors developing high-grade dysplasia or colorectal cancer within 5 years (top), and non-progressors remaining free from these (bottom).

Figure 2:. Representative endoscopic and histological images with copy number profiles.

Endoscopy images (upper right) and H&E (upper left) with genome-wide copy number profile below for representative non-progressor (A) and progressor (B) patients.

Figure 3:. Genomic alterations in non-progressor versus progressor LGD in discovery cohort.

A. Heatmap of genome-wide copy number alteration for lesions in the discovery LGD cohort, sorted by percent genome altered. Sporadic adenomas included below. B. Violin plots showing the number of altered genomic segments in progressor and non-progressor lesions. C. Genome-wide CNA frequency for non-progressor (NP, top) and progressor (P, bottom) patients. Stars indicate significant arm level differences at adjusted p-value p<0.01 level. For patients with multi-region analysis the most highly altered sample per patient was included.

Figure 4:. Model performance for prediction of future HGD/CRC.

A. Odds ratios for univariate models considering genomic score, UC-CaRE, and PSC variables. B. AUC values for genomic score alone at 5 years and PPV/NPV over time in validation data with 95% bootstrap confidence intervals. Kaplan-Meier progression-free survival for the discovery (C) and validation (D) cohorts using a univariate genomic score model. E. Odds ratios for multivariate model chosen using stepwise selection. F. AUC values for multivariate model at 5 years and PPV/NPV over time in validation data. G. Kaplan-Meier curves for validation data; high-risk (>0.5 risk) patients determined by multivariate model prediction.

Figure 5:. Phylogenetic analysis of multi-region data.

Phylogenetic trees (left) and matched copy number profiles (right) for (A) a representative non-progressor lesion and (B) a representative progressor lesion. Tree statistics for lesions in the discovery cohort that had at least 2 regions sequenced were maximum tree length (C), minimum tree length (D), clonal CNA (E), and average subclonal CNA (F).